Commercial applications and optimization of deep learning image recognition based on artificial intelligence

Abstract

In the current era of rapid development of artificial intelligence technology, the application of deep learning algorithms in the field of image recognition has become a key driving force for business innovation. Traditional image recognition methods, due to their insufficient efficiency and accuracy, are unable to meet the complex and variable requirements of business scenarios. This article focuses on the deep learning algorithms based on artificial intelligence, and deeply explores their specific applications in commercial fields such as precise diagnosis of medical images, efficient quality inspection of industrial products, and real-time monitoring of intelligent security. It demonstrates the value of enhancing business operation efficiency and quality. At the same time, in response to practical application challenges such as high data annotation costs and poor model robustness, research proposes optimization paths, covering technical means such as data augmentation, lightweighting of models, and transfer learning. Experiments show that the optimized algorithm significantly improves image recognition performance, providing practical guidance for the promotion of deep learning algorithms based on artificial intelligence in the commercial image recognition field.